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yaml_config="""
input_features:
-
name: Original_Title
type: text
level: word
encoder: t5
reduce_output: null
-
name: Keyword
type: text
level: word
tied_weights: Original_Title
encoder: t5
reduce_output: null
output_features:
-
name: Optimized_Title
type: sequence
level: word
decoder: generator
"""
with open("config.yaml", "w") as f:
f.write(yaml_config)
@pgrandinetti
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pgrandinetti commented Feb 7, 2021

@tthebimbolawal
When you dowload the file using the !wget instructions provided by Hamlet, the resulting csv will be named hootsuite_titles.csv, and it will be in the content folder, if you are using google-colab. See screenshot.
So, to load it in pandas you can do pd.read_csv('hootsuite_titles.csv')
I hope that answers your question.
Screenshot from 2021-02-07 17-39-44

@asktienlin
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asktienlin commented Apr 16, 2021

Hello all,

Thank you all for the information.
I have followed all steps and tried to make it work.

When I run the following code,
!ludwig predict --dataset hootsuite_titles_to_optimize.csv --model_path results/experiment_run/model/

It returns this error
FileNotFoundError: [Errno 2] No such file or directory: 'results/experiment_run/model/model_hyperparameters.json'

Could you all tell me what model path I should use to make it work?
Thank you a lot

@Suvakanta8
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Suvakanta8 commented Sep 8, 2021

Hii while I am trying to replace hootsuite_titles.csv dataset with my website dataset I am getting a value error like this:
ValueError: A Concatenate layer requires inputs with matching shapes except for the concat axis. Got inputs shapes: [(128, 32, 512), (128, 224, 512)]
please reply.......

@marcusbianco
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marcusbianco commented Sep 8, 2021

@Suvakanta8
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Suvakanta8 commented Sep 9, 2021

Thanks @marcusbianco can you please explain me how to prepare a dataset properly for training and the optimized score column in hootsuit dataset what is that ? Is that necessary for training?

@Suvakanta8
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Suvakanta8 commented Sep 9, 2021

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